Stop overthinking your AI prompts 🧠

In the year after ChatGPT was released, I remember noticing two new trends:

• Articles about “prompt engineers” being hired for hundreds of thousands of dollars just to write prompts
• Endless guides promising to teach you the secrets of writing the perfect ChatGPT prompt

My takeaway was that “prompting” must be really complex, and it was going to take a huge investment of time in order for me to get good at it.

(In case you’re unfamiliar: “prompting” just means “inputting text into a Large Language Model.” Or more simply: “typing into ChatGPT.”)

Since then, I’ve come to three conclusions about prompting:

• If you’re using a top-tier model (like GPT-4o or Claude Sonnet 3.5), you will often get good results regardless of how you write your prompt.
• However, a good prompt can make the difference between good results and great results.
• Following just a few basic prompting principles (below) will get you far!

📝 Simple tips for more effective prompts

Here are my top tips for getting better at prompting, and thus increasing the chance that you will get great results from an LLM:

Be very specific about what you want: How long should the answer be? What should the answer include? Who is the specific audience? What is the end goal of this task?

Ask it to iterate: Within a given conversation, the model will remember everything you’ve said and everything it has replied (until it reaches the end of its “context window”). Thus if you’re not 100% satisfied with its answer, then tell it exactly how you want to improve!

Give it a role: If you’re asking it a complex legal question (for example), you might get better results if you tell it to act like an expert lawyer. You can also use roles to adjust the writing tone of the results.

Give it examples: If you need the answer in a specific format, give the model a few examples of what the output should look like for a given input.

Ask it to think step-by-step: For complex tasks, guiding the model in how to approach the task step-by-step can result in better output. (The Claude documentation has a good example of this.)

Try a different model: Every LLM is different, so if one isn’t helpful for a particular task, then just try another! I’ve written previously about how to do this using Typing Mind.

🧠 Develop a mindset of abundance

I’ll leave you with one final tip from Ethan Mollick’s article, Getting started with AI: Good enough prompting:

You don’t need to ask for one email, ask for three in different tones to inspire you. You don’t need to ask for one way to complete a sentence, ask for 15 options and see if that unlocks your writing. Don’t ask for 5 ideas, ask for 30. In fact, our research found that GPT-4 can generate thousands of ideas before a large percentage of them start to overlap. Your job becomes one of pushing for variation (“give me ideas that are 80% weirder”), recombination (“combine ideas 12 and 16”) and expansion (“more ideas like number 12”), before selecting one you like.

Questions? Please let me know in the comments! 👇